A keyword or keyphrase is a word or set of terms submitted by a Web surfer to a search engine when searching for a related Web page/site on the World Wide Web (WWW). Search engines determine the relevancy of a Web site based on the keywords and keyword phrases that appear on the page/site. Since a significant percentage of Web site traffic results from use of search engines, Web site promoters know that proper keyword(s) selection is vital to increasing site traffic to obtain desired site exposure. Techniques to identify keywords relevant to a Web site for search engine result optimization include, for example, evaluation by a human being of Web site content and purpose to identify relevant keyword(s). This evaluation may include the use of a keyword popularity tool. Such tools determine how many people submitted a particular keyword or phrase including the keyword to a search engine. Keywords relevant to the Web site and determined to be used more often in generating search queries are generally selected for search engine result optimization with respect to the Web site.
After identifying a set of keywords for search engine result optimization of the Web site, a promoter may desire to advance a Web site to a higher position in the search engine's results (as compared to displayed positions of other Web site search engine results). To this end, the promoter bids on the keyword(s) to use with specific URL(s), wherein the bidding indicates how much the promoter will pay each time a Web surfer clicks on the promoter's listings associated with the keyword(s). In other words, keyword bids are pay-per-click bids for specific URL (Web site) promotion. The larger the amount of the keyword bid as compared to other bids for the same keyword, the higher (more prominently with respect to significance) the search engine will display the associated Web site in search results based on the keyword. Unfortunately, advertiser bidding terms may not be relevant to the Web site contents and, as a result, may not match the terms or language used by an end-user.
It may appear that the simplest way to verify a keyword(s) against a Web site (i.e., Web site content) is to use a conventional retrieval approach, which measures the similarity only between the keyword(s) and the Web site, without any additional data point comparisons. However, this technique is substantially limited. Even though the keyword(s) may be related to the Web site, the Web site itself may not include threshold criteria (e.g., direct match, number of occurrences, etc.) supporting the desired keyword(s), causing rejection of a potentially valuable bidding term. For example, consider that an online shopping corporation with an associated Web site bids on the phrase “online shopping”. If the conventional retrieval approach is used and a relatively small number of occurrences of the keyword “shopping” and no occurrence of keyword “online” are found in the Web site, the potentially valuable keyphrase of “online shopping” may be mistakenly disqualified as a bidding term.
Another conventional technique is to classify a submitted bid term/phrase and Web site to obtain two categories probabilities vectors, which are then combined into a final relevance score. The problem with this conventional technique is that it does not evaluate the term/phrase directly against his website, which can be substantially problematic. For example, if an advertiser bids on the term “Italian shoes”, and his website sells shoes but NOT Italian shoes, the conventional classification technique will indicate to the advertiser that the bid phrase of “Italian shoes” is irrelevant to the Web site.
In view of the above, systems and methods to better identify keywords relevant to Web site content would be welcomed by Web site promoters. This would allow the promoters to bid terms more likely to be used by an end-user. Ideally, these systems and methods would be independent of the need for a human being to evaluate Web site content to identify relevant keywords for search engine optimization and keyword bidding.